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Article

Effects of Obesity Treatment Type on Emotional Eating and Weight/Waist Circumference Changes in Women Through Interrelations of Induced Self-Regulation and Self-Efficacy

by
James J. Annesi
1,2,* and
Steven B. Machek
1
1
Kinesiology Department, California State University, Monterey Bay, Seaside, CA 93955, USA
2
Mind Body Wellbeing, LLC, Manahawkin, NJ 08050, USA
*
Author to whom correspondence should be addressed.
Obesities 2025, 5(4), 83; https://doi.org/10.3390/obesities5040083 (registering DOI)
Submission received: 24 October 2025 / Revised: 17 November 2025 / Accepted: 20 November 2025 / Published: 22 November 2025
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Abstract

Obesity is a medical issue of increasing prevalence, with emotional eating being a key contributor to the problem, particularly in women. Theory and previous research suggest that obesity treatment participants’ self-regulatory abilities and self-efficacy to control eating are viable targets for improving emotional eating and related impacts on an unhealthy body composition. However, an improved understanding of interrelations between self-regulatory and self-efficacy changes are needed to inform behavioral treatments, which have had mostly negligible effects beyond the short term. Women were randomized into 6-month community-based obesity treatment conditions of (a) cognitive–behavioral methods with attention on emotional eating (n = 48), (b) cognitive–behavioral methods with no specific attention on emotional eating (n = 48), and (c) weight loss education (n = 50). Study-related improvements were greater in the merged cognitive–behavioral condition (n = 96; aggregated because the two corresponding treatment conditions demonstrated no significant differences). Using data aggregated across all study participants, early change in eating-related self-regulation was a significantly stronger predictor of longer-term change in eating-related self-efficacy than vice versa. Consistent with that finding, paths from treatment condition→change in self-regulation→change in self-efficacy→change in emotional eating over both 6 and 12 months were significant but not where change in self-efficacy was, instead, entered as a predictor of self-regulation change. Lessened emotional eating was significantly associated with concurrent reductions in weight and waist circumference. Consistent with self-regulation theory, findings suggest benefits for cognitive–behavioral obesity treatments over the more common education-based approaches, as well as benefits for first focusing on self-regulation that could empower increases in self-efficacy. Consistent with self-efficacy theory, such induced increases might promote favorable behavioral changes.

1. Introduction

Obesity, or a body mass index (BMI) ≥ 30 kg/m2, is a medical issue of increasing prevalence [1]. Its associated health risks include type 2 diabetes, various cancers, liver and kidney disease, and sleep apnea [2]. Within the United States (U.S.), obesity in women ≥ 25 years of age is ~46% of the population, compared to ~42% of their male counterparts [1]. It is projected to continue its increase to 59% and 55% of the adults, respectively, by 2050. Although controlled eating will reduce excess weight in almost all affected, those behavioral changes have been exceedingly difficult to maintain beyond the short term [3,4]. Emotional eating (eating in response to negative mental states and/or mood) has been an important, possibly the most important, psychosocial correlate of obesity [5,6], especially in women [7,8]. Thus, better addressing that issue is essential in the quest for obesity reduction.
Many researchers suggest that an improved comprehension of psychosocial factors related to managing emotional eating, and overeating in general, should be better driven by theory and research [9,10,11]. However, others suggest that because behavioral methods have shown to be consistently inadequate for many decades, further behavior-change efforts should not be pursued [12]. Following from that premise, weight loss surgeries and pharmacologic methods, each with health risks of their own, are increasingly prominent as obesity treatment modalities [13,14]. While there is debate on the types of medications that will best serve disordered overeating in adults with obesity (e.g., glucagon-like peptide-1; lisdexamfetamine; and topirmate) [15,16], it is clear that more research is needed to determine their effects on psychological factors that could impact emotional eating. Research is also needed on their risks and benefits relative to those of behavioral methods [17,18].
Although positions on addressing the obesity epidemic vary, there is a consensus that, if there is any chance of impacting the problem through behavioral means, an improved understanding of associated psychological dynamics is required [4,11,19,20]. Also, on a population level, addressing obesity via surgeries or a lifetime of medications might be impractical due to their associated expenses and/or patients’ aversion to such invasive medical methods and/or their side effects [21]. Thus, effective, evidence-based behavioral processes that can be efficiently disseminated in a largescale and standardized manner might be the most favorable direction for many.
In efforts to address obesity and emotional eating through behavioral means, theories such as social cognitive theory [22] and self-regulation theory [23], as well as previous research [9,11,24,25], suggest advantages of a focus on increasing one’s ability to self-regulate through common challenges/barriers such as negative emotional states, high food availability, and social pressures. While the great majority of obesity treatments primarily educate participants on details related to the diet [20], others have been centrally focused on empowering self-regulatory skills such as cognitive restructuring and relapse prevention [9,10,26]. Self-efficacy theory [27], as well as past research [28,29,30], suggests that a focus on participants’ perceiving their own abilities via meaningful progress toward a goal (here, improved eating leading to body composition improvements) will be useful for advancing their commitment. Bandura [27] suggested that such self-efficacy gains may be enhanced via (a) mastery experiences (e.g., successfully negotiating personal challenges), (b) vicarious experience (e.g., viewing a like individual successfully completing the goal behavior), (c) verbal persuasion (e.g., hearing encouraging statements about one’s ability to progress), and (d) physiological/psychological states (e.g., positive mental states).
Interactions between changes in the psychosocial constructs of self-regulation and self-efficacy are, however, unclear [25] but increased clarity will be essential to better inform the focus of behavioral treatments. For example, if, as suggested by Bandura [31] and Conn [32], increases in self-regulatory skill usage promote self-efficacy, behavioral treatments concerned with addressing obesity via reductions in emotional eating should first focus on the building and rehearsal of self-regulatory skills (that would then promote enhanced self-efficacy via their induction of feelings of ability to counter previously overwhelming barriers). Conversely, as proposed by Kitsantas [33] and Vohs and Baumeister [23], if nurturing self-efficacy promotes self-regulation, its advancement through, for example, attention placed on mastery experiences, vicarious experience, verbal persuasion, and mental states would be an initial treatment task (that would then set conditions for improved absorption of self-regulatory skills). If there is no directionality in relationships identified, addressing both self-regulation and self-efficacy simultaneously, with similar effort, would be indicated. While some reciprocity between changes in self-regulation and self-efficacy could be expected [34], it is through engaging research gaps such as the directionality of their relationship where findings could meaningfully advance progress in emotional eating and its association with an improved body composition and reductions in health risks. Both behavioral and medical scientists suggest a necessity for such refinements to inform both theory and application [35,36].
Thus, within this study, women with obesity were randomized into one of three differing community-based treatment conditions over 6 months incorporating non-surgical/non-pharmacological means. They were assessed on changes in eating-related self-regulation, eating-related self-efficacy, emotional eating, and body composition at intervals from treatment start to month 12. In addition to weight, weight circumference was included as a measure of body composition based on its indicated advantages for the prediction of health risks [37]. It was expected that the cognitive–behavioral treatment approaches would demonstrate greater advancements in the measured psychosocial and physiological factors than an educational approach, and a treatment emphasis on addressing emotional eating would be associated with further reductions on that measure. It was left as a research question whether the prediction of longer-term self-efficacy change by earlier change in self-regulation would be stronger than the reverse direction in bivariate analyses and within theory-driven paths toward change in emotional eating. It was expected that lowered emotional eating would be significantly associated with reductions in both weight and waist circumference.

2. Materials and Methods

2.1. Participants

Participant data were from ongoing field research in the U.S. contrasting weight-management methods in community settings [11]. Although aspects of the data set were previously analyzed, the present research focus was exclusive to this study. Inclusion requirements for the female sample with obesity were (a) age ≥ 21 years, (b) no medical contraindication or restriction for participation, (c) no change in a psychotropic medication over the previous 6 months, and (d) no participation in a weight loss program/medical obesity intervention over the previous 12 months. The overall sample size was based on an a priori analysis (see the Data Analyses subsection below). Based on block randomization associated with the participating community health facilities, there were 48 participants initiating the cognitive–behavioral treatment with attention allocated to emotional eating, 48 participants in the cognitive–behavioral treatment without specific attention paid to emotional eating, and 50 participants in the treatment focused on weight-management education. There was no significant group difference at baseline on age (Moverall = 47.4 years, SD = 8.9), BMI (Moverall = 35.0 kg/m2, SD = 3.3), racial/ethnic make-up (overall 78% White, 15% Black, 5% Hispanic, and 2% other), and number of dropouts prior to treatment start (overall N = 14). The median reported family income during the previous year was USD 72,500 (almost all participants were within a middle income range) and 68% of the overall sample had a bachelor’s degree or greater. Based on a ratio of sessions attended/possible sessions, the participants’ overall treatment attendance was 84.2% (SD = 11.1), which did not significantly differ by group. A university institutional review board approved the research protocol and the informed consent process that required a signature from each participant prior to starting any study activity. Ethical and privacy requirements of the World Medical Association Helsinki Declaration and the American Psychological Association were upheld.

2.2. Measures

Self-regulation for eating (S-Reg) was measured using the 10 items of the Eating-Related Self-Regulation Scale [38]. Items reflected usage of self-regulatory/self-management skills proposed by Michie et al. [39] as being consistent with social cognitive theory [22]. A sample item is, “I make formal agreements with myself regarding my eating.” Item response options ranged from 1 (never) to 4 (often) and were summed. The reported internal consistency was Cronbach’s α = 0.79 (present sample, α = 0.75), with 2-week test–retest reliability at 0.78 [38]. Predictive validity was suggested by associations of score increases with reductions in measures of body composition [38].
Self-efficacy for controlling eating (S-Eff) was measured using the 20 items of the Weight Efficacy Lifestyle Scale [28]. Confidence at persevering with controlled eating when under challenging conditions/stimuli (i.e., negative emotions, physical discomfort, social pressure to eat, high food availability, and positive activities) had item response options ranging from 0 (not confident) to 9 (very confident) and were summed. A sample item is, “I can resist eating when I am anxious (nervous).” The reported internal consistency ranged from Cronbach’s α = 0.70 to 0.90 [28] (present sample, α = 0.75). Predictive validity was indicated through score correspondences with perceptions of control over one’s eating [40] and weight reduction [41].
Emotional eating (EmE) was measured using 15 items of the Emotional Eating Scale [42]. Propensity to eat when prompted by the adverse mood dimensions of depression, anxiety, and/or anger/frustration had item response options ranging from 0 (no desire to eat) to 9 (an overwhelming urge to eat) and were summed. A sample item is [a propensity to eat when] “nervous.” The reported internal consistency ranged from Cronbach’s α = 0.72 to 0.79 (present sample, α = 0.74), with 3-week test–retest reliability at 0.79 [42]. Convergent and discriminant validity was suggested through score correspondences with binge eating [43] but not general psychopathology [42].
Body weight was measured to the nearest 0.10 kg using a digital floor scale (Health o meter Professional Model-800KL; McCook, IL, USA) that was calibrated the same day of measurement. Outer clothing (e.g., jacket) and shoes were removed by the participant prior to measurement. Waist circumference was measured to the nearest 0.10 cm at the midpoint between the participant’s last rib and iliac crest during minimal respiration using a circumferential measuring tape (Seca Model-201; Chino, CA, USA).

2.3. Procedure

Treatment instructors were current staff members of the participating facilities. Each had at least one national/international certification in health promotion methods and were trained by study staff in only one treatment within this study. Each of the three treatment types lasted 6 months, requiring 11 total participant/hours each. Participants understood that the focus of their treatment was weight reduction. Procedures of the two cognitive–behavioral treatment conditions were guided by social cognitive theory [22], self-efficacy theory [27], and self-regulation theory [23]. More specifically, methods focused on addressing their key tenets, which suggested that individuals can overcome challenges to goal attainment under situations that enable self-regulating through lifestyle challenges (i.e., increased self-regulation) and enhanced feelings of competence (i.e., increased self-efficacy). Self-regulation methods included proximal goal setting, cognitive restructuring, relapse prevention, and stimulus control. Adapted from processes certified by the National Institutes of Health/National Cancer Institute of the U.S. [44], the skills were enabled and rehearsed initially through a physical activity context so that increased eating-related self-regulation would attain and sustain weight loss. In efforts to increase self-efficacy, eating-related progress was systematically tracked on a provided grid and acknowledgement of even minor amounts of progress was emphasized by instructors. Based on theory [27], that method addressed the mastery experience element of increasing self-efficacy by acknowledging participants’ success at negotiating their challenges and barriers. The other proposed aspects for increasing self-efficacy (i.e., vicarious experience, verbal persuasion, and physiological/psychological states [27]) were also focused upon during the treatment contents to a lesser extent. Thus, processes addressing both self-regulation and self-efficacy were addressed throughout the treatments. In one of the cognitive–behavioral treatment conditions, 20% of treatment time was directed at emotional eating. In the second cognitive–behavioral treatment condition, emotional eating was not specifically addressed. Small group meetings were held every 2 weeks.
Procedures within the weight-management education treatment condition were guided by the health belief model [45]. That theory suggests that individuals seeking a goal such as weight reduction will improve their self-management/self-regulation of eating through education on nutrition and the benefits of controlling their eating and a healthy diet. Current iterations of the health belief model additionally indicate that self-efficacy and its associated behavioral persistence will be enhanced as increased knowledge fosters actions leading to goal-related successes and feelings of competence that follow [45]. After an initial one-on-one session overviewing the overall treatment content, written educational materials [46] were adapted and provided to participants every 2 weeks. Each segment was supported within 3 days of its completion by an in-person or phone communication with an instructor to clarify its contents and address questions.
For all groups, completion of self-selected methods of physical activity/exercise were encouraged, as was weekly self-weighing. Fidelity monitoring was conducted by non-instructional study staff using a structured form that assessed adherence to elements specific to each treatment protocol. Fidelity assessments were applied to 10% of sessions using in-person observations. Scores indicated very strong protocol adherence. Minor protocol compromises were addressed through rater–treatment instructor interactions. Non-instructional staff also administered study measures to participants in a private area at each designated time point.

2.4. Data Analysis

Based on the criteria indicated by White et al. [47], there was no systematic bias in presence/absence of participants’ 12% of overall missing data (all occurring beyond baseline). The concomitant classification of missing at random fulfilled the criteria required for use of the expectation-maximization algorithm for imputation [48,49] and, thus, an intention-to-treat analysis was enabled. Based on the primary regression analysis and evaluation of reciprocal models, a minimum sample size of 145 was required to detect the small–moderate effect of Cohen’s f2 = 0.10 at the conservative statistical power of 0.90, α < 0.05 [50]. Variance inflation factor values < 2.0 indicated acceptable multicollinearity, with neither floor nor ceiling effects found.
Mixed-model repeated measures ANOVAs first assessed overall changes in the study measures over the designated intervals, then whether those changes significantly differed by the treatment conditions of (a) cognitive–behavioral methods—emotional eating attention, (b) cognitive–behavioral methods—no specific attention on emotional eating, and (c) weight-loss education. Using data aggregated across treatment conditions, bivariate regression analyses then assessed whether the strength of the prediction of 6-month change in S-Eff by 3-month change in S-Reg and 6-month change in S-Reg by 3-month change in S-Eff significantly differed. Those analyses were additionally completed with 12- and 6-month changes in place of the 6- and 3-month change intervals, respectively. Next, significance of paths from group→3-month change in S-Reg→6-month change in S-Eff→6-month change in EmE and, reciprocally, group→3-month change in S-Eff→6-month change in S-reg→6-month change in EmE were assessed, controlling for baseline EmE. Similar to the bivariate analyses, additional paths were fit with 12- and 6-month changes entered in place of the 6- and 3-month changes, respectively. Finally, associations of 6- and 12-month changes in EmE with changes in weight and waist circumference during the same durations were calculated, also controlling for baseline EmE.
IBM SPSS Statistics version 28.0 was used for the statistical testing, integrating the Process 4.2 macroinstruction Model 6 with 10,000 percentile-based bootstrap resamples [51]. Statistical significance was set at α < 0.05 (two-tailed) throughout. Where bootstrapping was incorporated, a 95% confidence interval (95% CI) assessed statistical significance. Based on suggestions for the present type of theory-based research [52,53], there was no statistical adjustment for multiple comparisons.

3. Results

3.1. Group-Based Score Changes

There was no significant difference in 6- or 12-month changes in EmE between the two cognitive–behavioral treatments either including specific attention on emotional eating (M = −9.90 [SD = 9.67] and M = −9.04 [SD = 10.56], respectively) or no such attention to emotional eating provided (M = −9.65 [SD = 9.81] and M = −8.96 [SD = 10.64], respectively); F(1, 94) = 0.02, p = 0.900, and F(1, 94) = 0.001, p = 0.969, respectively. There was also no significant difference between those two conditions on 3- and 6-month changes in S-Reg and S-Eff; ps > 0.700. Therefore, data across the two cognitive–behavioral treatment conditions were merged for further analyses. They were coded 1 = (now merged) cognitive–behavioral treatment (n = 96) and 0 = weight loss education treatment. Within the two-group analyses, improvements in all psychosocial and body composition measures were significant overall and significantly more pronounced in the merged cognitive–behavioral treatment group (Table 1). The one exception was with 12-month change in EmE, where the greater improvement in the cognitive–behavioral condition did not reach statistical significance (p = 0.113).

3.2. Directionality in the S-Reg↔S-Eff Change Relationships

Incorporating aggregated data (N = 146), the prediction of 6-month change in S-Eff by 3-month change in S-Reg (β = 0.59) was significantly stronger than the reciprocal prediction of 6-month change in S-Reg by 3-month change in S-Eff (β = 0.42); z = 1.97, p = 0.049. However, the stronger prediction of 12-month change in S-Eff by 6-month change in S-Reg (β = 0.57) than the reciprocal prediction of 12-month change in S-Reg by 6-month change in S-Eff (β = 0.55) did not reach statistical significance; z = 0.22, p = 0.824.

3.3. Contrasting Directionality Across Proposed Paths

The path from group→3-month change in S-Reg→6-month change in S-Eff→6-month change in EmE was significant; B = −0.73, SEB = 0.33, 95% CI [−1.520, −0.203] (Figure 1A). However, the reciprocal path from group→3-month change in S-Eff→6-month change in S-Reg→6-month change in EmE was not significant; B = −0.04, SEB = 0.11, 95% CI [−0.281, 0.167] (Figure 1B). In contrast with findings given within the Group-Based Score Changes subsection (above), the direct effect of group on EmE change was not significant in either of the above models that accounted for interactions between the S-Reg and S-Eff changes; B = 1.74, SEB = 1.29, 95% CI [−4.288, 0.818], and B = −2.34, SEB = 1.31, 95% CI [−4.926, 0.240], respectively.
Additionally, the path from group→6-month change in S-Reg→12-month change in S-Eff→12-month change in EmE was significant; B = −1.62, SEB = 0.53, 95% CI [−2.836, −0.715] (Figure 2A). The reciprocal path from group→6-month change in S-Eff→12-month change in S-Reg→12-month change in EmE was again not significant; B = −0.02, SEB = 0.28, 95% CI [−0.603, 0.516] (Figure 2B). The direct effect of group on EmE change was also not significant in either of the above models; B = −0.09, SEB = 1.41, 95% CI [−2.877, 2.690], and B = 0.17, SEB = 1.50, 95% CI [−2.798, 3.145], respectively.

3.4. Association of Reduced EmE with Weight/Waist Circumference Reductions

Decrease in EmE over 6 months was significantly associated with 6-month reductions in weight and waist circumference (βs = 0.56 and 0.53, respectively, ps < 0.001). Lessened EmE over 12 months was significantly associated with 12-month reductions in weight and waist circumference (βs = 0.55 and 0.58, respectively, ps < 0.001).

4. Discussion

Findings addressed gaps concerning behavioral obesity treatment foci, with attention directed toward EmE [54]. A cognitive–behavioral treatment approach focused on enhancing eating-related S-Reg and S-Eff was associated with more improvement in those factors, EmE, and measures of body composition when contrasted with a more commonly applied weight loss education methodology [20]. Within the cognitive–behavioral conditions, findings suggested no advantage of directly addressing emotional eating over addressing controlled eating more generally. Extensions of this research should evaluate participants identified as having a high degree of EmE to determine if the present outcomes differ. The present findings are consistent with previously identified limitations of weight loss education informed by the health belief model [55] and benefits of cognitive–behavioral approaches supported by social cognitive theory [56]. It should be noted, however, that the addition of S-Eff (via self-efficacy theory [27]) to interventions based on the health belief model might add to its viability [45]. EmE, too, has responded well to cognitive–behavioral approaches, although, unlike in the present research, most (but not all [57]) have been via expensive individualized modalities [58,59].
The finding that, over the longer 12-month period, improvement in EmE within the cognitive–behavioral condition was not significantly greater than that of the educational condition was unexpected. Possibly, more attention paid to methods to directly address EmE (e.g., self-regulatory skills development specifically targeting prompts to emotion-related eating)—especially beyond the initial 6 months where the expected weight loss might be most reinforcing [4]—will be required to foster more long-term improvement. Analyses of what specific S-Reg skills are most productive at that time will also require direct research. Social cognitive theory [22], which was utilized here to guide the cognitive–behavioral treatment processes, has been criticized for failing to provide predictions relating to the temporal aspects of behavioral changes [60].
This research was unique in suggesting directionality within changes in eating-related S-Reg and S-Eff. Although theory indicated that each possible direction could be supported (as well as simply a bi-directional, reciprocal relationship) [22,23], the current findings suggested that 3-month change in S-Reg better predicted 6-month change in S-Eff than vice versa. However, that significant difference did not remain in predictions over 12 months. It is possible S-Reg is most beneficial in overcoming early perceptions of behavioral challenges. It should also be noted that 3-month improvements in S-Eff were substantially greater than 6-month gains (possibly, where confidence in controlling one’s eating was reflected upon more realistically as longer amounts of time pass). Implications of that dissonance within the present relationships are unclear and warrant future direct investigation. Regardless, findings suggest that, within the present context, there are benefits of a treatment focus on S-Reg skills building to empower longer-term progress in S-Eff and behavioral change. It will continue to be advantageous to experiment with refinements of behavioral weight loss treatments toward their most-relevant components in order to maximize both effects and efficiency [61].
The path analyses additionally suggested directionality from S-Reg changes to changes in S-Eff. In fact, that relationship appeared to be so salient that the effect of treatment condition on EmE over 6 months (Table 1; time × group effects) no longer looked to be significant when the S-Reg-S-Eff change relationship was accounted. That finding reinforced the previously proposed viability of both S-Reg and S-Eff within a treatment context [25,30], as well as their interrelationship. Thus, the aforementioned suggestion that an initial treatment focus on S-Reg supports lasting S-Eff improvements was strengthened. It appeared that effect sizes of S-Reg of eating changes demonstrated a marginal increase from 3- to 6-month changes within the cognitive–behavioral condition, while S-Eff substantially decreased beyond its 3-month change in both treatment types. While the observed increase in S-Reg skills usage could be attributed to participant practice (as suggested through the strength model of self-regulation [62]), the identified reductions in initial S-Eff progress could also be posited based on theory [27]. Propositions suggest that realistic goals for controlling one’s eating should be strongly advocated, which could temper risks for dropout when feelings of ability wane due to perceived non-attainment of (often unrealistic) expectations early in treatment [63].
Findings related to the significant association of lowered EmE with weight and waist circumference reduction were expected. It is notable that the more-productive cognitive–behavioral treatment condition was associated with mean reductions in weight and waist circumference of 6.0% and 5.7%, respectively, over 6 months and 5.8% and 5.3%, respectively, over 12 months. Unlike educationally based treatment-associated reductions of 1–2% across measures and times, their decreases are consistent with reduced health risks [64].

Limitations

Even given the treatment implications for the present findings and production of additional research questions for extensions of this investigation, limitations were present. For example, the present study had (a) a lack of a true control condition that could have protected from social support, expectation, and other experimental effects, (b) a dependence on self-report measurement (except for body composition), and (c) a specific volunteer sample primarily limited to well-educated White women of at least a middle income level. Thus, generalizability of findings might be restricted because of those characteristics. The constructs of S-Eff and S-Reg, while distinct theoretically [22,23], might partially reflect similar processes. Thus, extensions of this research should both test for such a relationship and also explore constructs which emanate from other behavior-change theories. Also, there was some temporal overlap in relationships within the path models (e.g., 6-month change in S-Eff predicting 6-month change in EmE). Extensions of this research should test for bidirectional effects there, which could have treatment-suggestion implications. Additionally, although the regain of weight and decline in psychosocial predictors of weight management behaviors was less than those typically identified within behavioral treatments [3,4,19,20], some regain of weight and reduction in favorable psychosocial states was observed. Thus, replications over longer time frames will be required to better assess longitudinal effects. This is especially important for evaluation of reductions in health risks that are resilient over time. Finally, because the treatments were administered through interpersonal means, variability across instructor characteristics (e.g., demographic and behavioral) could have affected outcomes.

5. Conclusions

It is hoped that theory- and research-based investigation into the psychosocial dynamics related to EmE and the behavioral control of obesity address the present shortcomings and contribute to informing scalable obesity treatments. Such was the aim here. Continuing that type of research within settings where interventions may be readily applied, including in association with pharmacological and/or surgical approaches, might also facilitate meaningful effects on the epidemic of obesity that is projected to impact more than half the U.S. adult population within just several years.

Author Contributions

J.J.A. conceptualized the study, analyzed the data, and wrote the initial draft. S.B.M. contributed to the data interpretation and revised the article for important intellectual content. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Institutional Review Board of Kennesaw State University (013173), 7 May 2021.

Informed Consent Statement

Informed consent for participation was obtained from all participants involved in the study.

Data Availability Statement

The data supporting the conclusions of this article will be made available by the first author upon reasonable request.

Conflicts of Interest

Author James J. Annesi was employed by the company Mind Body Wellbeing, LLC. The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Paths of the prediction of 6-month change in emotional eating by group, through earlier change in self-regulation predicting longer-term change in self-efficacy (A) and through self-efficacy change predicting change in self-regulation (B). Group is coded 1 = cognitive–behavioral treatment, 0 = weight loss education treatment. Path data are given as unadjusted beta, (its associated standard error), and [95% confidence interval]. Significant paths are given in bold type.
Figure 1. Paths of the prediction of 6-month change in emotional eating by group, through earlier change in self-regulation predicting longer-term change in self-efficacy (A) and through self-efficacy change predicting change in self-regulation (B). Group is coded 1 = cognitive–behavioral treatment, 0 = weight loss education treatment. Path data are given as unadjusted beta, (its associated standard error), and [95% confidence interval]. Significant paths are given in bold type.
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Figure 2. Paths of the prediction of 12-month change in emotional eating by group, through earlier change in self-regulation predicting longer-term change in self-efficacy (A) and through self-efficacy change predicting change in self-regulation (B). Group is coded 1 = cognitive–behavioral treatment, 0 = weight loss education treatment. Path data are given as unadjusted beta, (its associated standard error), and [95% confidence interval]. Significant paths are given in bold type.
Figure 2. Paths of the prediction of 12-month change in emotional eating by group, through earlier change in self-regulation predicting longer-term change in self-efficacy (A) and through self-efficacy change predicting change in self-regulation (B). Group is coded 1 = cognitive–behavioral treatment, 0 = weight loss education treatment. Path data are given as unadjusted beta, (its associated standard error), and [95% confidence interval]. Significant paths are given in bold type.
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Table 1. Descriptive statistics and mixed-model repeated measures ANOVA results.
Table 1. Descriptive statistics and mixed-model repeated measures ANOVA results.
MeasureEffect for Time Time × Group Effect
Treatment GroupF(1, 144)pη2pMSDMSDMSDF(1, 144)pη2p
BaselineMonth 3Baseline-Month 3 change
Self-regulation for eating122.43<0.0010.46 8.34<0.0010.06
   Cognitive–behavioral methods 23.515.1530.984.557.476.60
   Weight loss education methods 22.505.6426.885.384.385.13
   Aggregated data 23.165.3229.585.216.416.30
Self-efficacy for controlling eating1605.03<0.0010.92 4.870.0290.03
   Cognitive–behavioral methods 22.256.38113.0927.2490.8424.87
   Weight loss education methods 22.257.87103.6027.7381.3624.21
   Aggregated data 22.256.90109.8427.6887.5924.97
BaselineMonth 6Baseline–Month 6 change
Self-regulation for eating131.11<0.0010.53 20.30<0.0010.12
   Cognitive–behavioral methods 23.515.1532.423.778.916.35
   Weight loss education methods 22.505.6426.725.444.385.13
   Aggregated data 23.165.3230.475.177.306.32
Self-efficacy for controlling eating98.45<0.0010.41 15.53<0.0010.10
   Cognitive–behavioral methods 22.256.3831.707.209.447.94
   Weight loss education methods 22.257.8726.328.004.087.57
   Aggregated data 22.256.9029.867.887.618.19
Emotional eating102.79<0.0010.42 10.140.0020.07
   Cognitive–behavioral methods 27.717.9917.948.28−9.779.70
   Weight loss education methods 25.109.6620.009.69−5.105.05
   Aggregated data 26.828.6518.648.81−8.178.67
Weight (kg)165.75<0.0010.54 50.57<0.0010.26
   Cognitive–behavioral methods 95.1611.8689.4411.70−5.723.59
   Weight loss education methods 96.2110.0294.569.61−1.652.58
   Aggregated data 95.5211.2491.1911.26−4.333.80
Waist circumference (cm)75.91<0.0010.35 52.67<0.0010.27
   Cognitive–behavioral methods 106.389.27100.309.76−6.074.57
   Weight loss education methods 105.557.86105.008.09−0.553.91
   Aggregated data 106.098.79101.919.46−4.185.08
BaselineMonth 12Baseline–Month 12 change
Emotional eating76.39<0.0010.35 2.550.1130.02
   Cognitive–behavioral methods 27.717.9918.719.09−9.0010.54
   Weight loss education methods 25.109.6618.889.97−6.228.81
   Aggregated data 26.828.6518.779.37−8.0510.04
Weight (kg)81.89<0.0010.36 31.43<0.0010.18
   Cognitive–behavioral methods 95.1611.8689.6311.96−5.534.35
   Weight loss education methods 96.2110.0294.9110.34−1.304.28
   Aggregated data 95.5211.2491.4411.67−4.084.76
Waist circumference (cm)52.24<0.0010.27 30.39<0.0010.17
   Cognitive–behavioral methods 106.389.27100.7110.32−5.665.42
   Weight loss education methods 105.557.86104.798.33−0.764.41
   Aggregated data 106.098.79102.119.85−3.985.59
Cognitive–behavioral method group, n = 96. Weight loss education methods group, n = 50. Aggregated data, N = 146. η2p = partial eta-squared (SSEffect/[SSEffect + SSError]).
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Annesi, J.J.; Machek, S.B. Effects of Obesity Treatment Type on Emotional Eating and Weight/Waist Circumference Changes in Women Through Interrelations of Induced Self-Regulation and Self-Efficacy. Obesities 2025, 5, 83. https://doi.org/10.3390/obesities5040083

AMA Style

Annesi JJ, Machek SB. Effects of Obesity Treatment Type on Emotional Eating and Weight/Waist Circumference Changes in Women Through Interrelations of Induced Self-Regulation and Self-Efficacy. Obesities. 2025; 5(4):83. https://doi.org/10.3390/obesities5040083

Chicago/Turabian Style

Annesi, James J., and Steven B. Machek. 2025. "Effects of Obesity Treatment Type on Emotional Eating and Weight/Waist Circumference Changes in Women Through Interrelations of Induced Self-Regulation and Self-Efficacy" Obesities 5, no. 4: 83. https://doi.org/10.3390/obesities5040083

APA Style

Annesi, J. J., & Machek, S. B. (2025). Effects of Obesity Treatment Type on Emotional Eating and Weight/Waist Circumference Changes in Women Through Interrelations of Induced Self-Regulation and Self-Efficacy. Obesities, 5(4), 83. https://doi.org/10.3390/obesities5040083

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